Page 62 - AI Standards for Global Impact: From Governance to Action

AI Standards for Global Impact: From Governance to Action

9�4 How AI transforms disaster management

Real-world case studies from the ongoing activities of the WMO-led Working Group on Digital
Transformation for Hydrology and Water Resources highlight the capabilities of AI-driven
tools such as route optimization for responders, flood forecasting, and user-centric chatbots
elevatinge situational awareness and decision-making are highlighted.

AI enhances disaster management and climate risk prediction through human-centred,
standards-driven approaches. This is achieved by systemic views of climate impacts, spatial
prediction using deep learning, and the integration of geospatial, meteorological, and socio-
economic data. Key themes include early warning systems, LLMs for communication, and
federated learning to build equitable, global AI solutions.

The AI tool, SukhaRakshakAI (Anticipatory Drought Intelligence for a Climate-Resilient Future)
empowers farmers and drought managers with early forecasts and localized advisories.
SukhaRakshakAI aims to address global drought challenges such as weak early warning
systems and poor data availability, while highlighting historical impacts on agriculture. Built on
prediction, preparation, and protection, the system integrates multi-source data, AI models like
Gemini and AI4Bharat, and multilingual support.

The United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) works to
improve data use in humanitarian response through four streams: Data Science, Responsibility,
Services, and Learning. The Humanitarian Data Exchange (HDX) platform hosts 20,000 datasets
and supports crises like COVID-19. UNOCHA leverages AI for climate forecasting, anticipatory
action, and early warnings, emphasizing responsible governance and ethics.

The development of digital twin technology using satellite data, illustrated through a case
study in the Kingdom of Tonga by United Nations Office for Outer Space Affairs (UNOOSA).
UNOOSA plays a pivotal role in maintaining the UN Space Registry, advancing global
development through space science, and providing technical expertise and training. Through
its UN-SPIDER platform, UNOOSA ensures universal access to space-based information for
disaster management, covering the entire disaster management cycle. The implementation
of digital twin technology, particularly through high-resolution satellite imagery and advanced
AI algorithms, provides a dynamic and detailed representation of the real world which helps
users understand the impact of rising sea levels. This technology can also aid decision-makers
in disaster preparedness and response by simulating potential disasters from rising sea levels.
The Tonga Disaster Preparedness Pilot Project demonstrates how remote sensing and digital
twin technology can simulate disaster scenarios to assess potential damage and improve
preparedness strategies. By combining satellite imagery and AI, digital twins create detailed,
cost-effective 3D models compared to unmanned aerial vehicles (drones). UNOOSA also
integrates IoT sensors with digital twin technology to optimize evacuation planning and support
data-driven infrastructure planning.

For Tongatapu Island, Kingdom of Tonga, these digital twin products allow the identification
of vulnerable coastal areas and contribute to planning evacuation routes, reinforcing coastal
defences, and developing disaster-resilient infrastructure. The digital twin can serve as a
collaborative platform for national government agencies, local communities, and disaster
response teams. By enabling them to interact with the same data and models, stakeholders
can plan and execute disaster response strategies more efficiently. The digital twin could also

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